3928 results for "RNA AND sequencing OR transcriptome"

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• Single Cell MK and HSC sequencing

  In the current understanding of adult bone marrow hematopoiesis, megakaryocytes (MKs) originate from cells immuno-phenotypically indistinguishable from hematopoietic stem cells (HSCs), bypassing intermediate progenitors. Here, we use single cell RNA sequencing to characterize HSCs and MKs from human bone marrow, to investigate MK lineage commitment and maturation.

  Study EGAS00001004844

• Single-Cell RNA Sequencing of Terminal Ileal Biopsies Identifies Signatures of Crohn’s Disease Pathogenesis

  Biopsies from the terminal ileum of healthy individuals and terminal ileum of Crohns disease patients are collected and processed single cells and processed for single-cell RNA-sequencing using 10X Genomics 3' v3 and v3.1 and Illumina sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001015692

• Single nucleus and in situ RNA sequencing reveals cell topographies in the human pancreas

  Molecular evidence of cellular heterogeneity in the human exocrine pancreas has not been established, due to the local concentration of hydrolytic enzymes that can rapidly degrade cells and RNA upon resection. Here we innovated single-nucleus RNA sequencing protocols, and profiled more than 120,000 cells from adult and neonatal human donors to create the first comprehensive atlas of human pancreas cells, including epithelial and non-epithelial constituents. Adult and neonatal pancreata shared common features, including the presence of previously undetected acinar subtypes, but also showed marked differences in the composition of the endocrine, endothelial, and immune compartments. Spatial cartography, including cell proximity mapping through in situ sequencing, revealed dynamic developmental cell topographies in the endocrine and exocrine pancreas. Our human pancreas cell atlas can be interrogated to understand pancreatic cell biology, and provides a crucial reference set for future comparisons with diseased tissue samples to map the cellular foundations of pancreatic diseases.

  Study EGAS00001004653

• Genomic (WGS) data for the validation of the glioblastoma progression study (GBMatch).

  43 low-coverage genomes derived from fresh-frozen glioblastoma tumor samples. These genomes have been produced for validation purposes and match the corresponding RRBS and RNA-seq profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004077

• KNS42 and SF188 H3K36me3 chipSeq

  Chromatin immunoprecipitation (ChIP) was carried out employing antibodies against H3K36me3 and RNA polymerase II using the HistonePath and TranscriptionPath assays by ActiveMotif. Whole genome sequencing was carried out using an Illumina HiSeq2000 and data is provided as 6 BAM files. H3K36me3 chipseq RNA polymerase II chipseq and input coverage for each cell line.

  Dataset EGAD00001004119

• Sequencing data for oesophageal and related samples - Abbas et al (RNA)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (RNA for 197 samples)

  Dataset EGAD00001011269

• NHGRI GREGoR Consortium: Genomics Research to Elucidate the Genetics of Rare Disease

  The NHGRI GREGoR (Genomics Research to Elucidate the Genetics of Rare Disease) Consortium was established in June 2021 with the goal of developing novel tools and approaches to advance the discovery of the genetic basis of rare conditions. Numerous types of molecular data are generated in GREGoR and available on the AnVIL cloud platform via dbGaP application, including short- and long-read genome and exome sequencing, transcriptomics, metabolomics, methylomics, and proteomics. De-identified clinical and demographic data is obtained, with a focus on standardized ontologies.Visit the GREGoR Consortium data webpage for summary information about the GREGoR Dataset, including numbers of participants and data types, methods documentation, and Release Notes. The Consortium comprises five Research Centers (RCs - see below), a Data Coordinating Center (DCC), and various partner members and external collaborators.Baylor College of Medicine Research Center (BCM-GREGoR) The Baylor College of Medicine GREGoR program, which is part of the GREGoR consortium, enrolls individuals, families, and cohorts with suspected rare disease across a range of syndromic and non-syndromic phenotypes. Subjects are enrolled from national and international collaborating physician referrals. Subjects provide written informed consent for future re-contact. Data generated and shared include family structure, detailed phenotypes, exome or short-read genome data, and in some cases long-read genome or RNA-sequencing, and these are shared upon completion of standard quality control checks and annotation. Broad Institute (Broad) The Broad Center for Mendelian Genomics, part of the GREGoR consortium uses next-generation sequencing (exome, genome, transcriptome, and long read sequencing), computational approaches, and functional studies to discover the variants and genes that underlie Mendelian conditions with a particularly focus on neuromuscular, neurodevelopmental, and syndromic phenotypes. Samples come from collaborators and direct enrollment through the Rare Genomes Project and we are committed to rapid data sharing without an embargo period. University of California, Irvine (UCI-GREGoR) To accelerate the pace of Mendelian disease gene discovery and clinical implementation, we propose a Mendelian Genomics Research Center, part of the GREGoR Consortium, leveraging the broad pediatric and adult clinical and research expertise at Children's National Hospital and University of California, Irvine. Our goal is to develop best practices to increase the diagnostic yield of rare diseases, engage the community to reduce health disparities for complex diagnoses, while creating a dataset accessible to all. Our Center will unite world class experts combining basic and translational research with innovative approaches to phenotyping, variant identification and functional investigation of both coding and non-coding sequence changes with the goals of discovering novel Mendelian gene variations and identifying variants not detected on current sequencing pipelines, disambiguating uncertain variants into disease-causing versus benign categorizations, and sharing information by working collaboratively with the GREGoR community.GREGoR Stanford Site (GSS) The goal of the GREGoR Stanford Site (GSS) is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease. Participants included individuals with undiagnosed suspected Mendelian disease who had non-diagnostic exome sequencing and their immediate family members. Participants and their family members provided written, informed consent and biological samples from which DNA, RNA, plasma, fibroblasts, PBMCs and other cell types were generated and stored. Samples from research participants and their immediate family members may have undergone short and long-read genome sequencing, transcriptome sequencing, metabolomics and/or lipidomics profiling, methyl-capture-sequencing and ATAC-sequencing. De-identified clinical data extracted from participant medical records are linked to the samples. University of Washington Center for Rare Disease Research (UW-CRDR) The goals of the University of Washington Center for Rare Disease Research are to: (1) maximize novel gene discovery for Mendelian conditions by recruitment, short- and long-read whole genome sequencing, transcriptome sequencing and analysis of families with rare conditions for which the gene is either unknown or the gene is known but no pathogenic variant can be identified via clinical testing; (2) develop new strategies for gene discovery for Mendelian conditions caused by variants that are difficult to detect using conventional testing strategies, variants of unknown function effect (e.g., regulatory, structural variants) or have unusual modes of inheritance; and (3) implement high-throughput screening and targeted follow-up functional studies to prioritize and validate candidate non-coding variants. De-identified data and phenotypic information are shared via MyGene2, ClinVar, and AnVIL.

  Study phs003047

• Performance assessment of Total RNA sequencing of human biofluids and extracellular vesicles

  Study EGAS00001004428

• Whole Exome and RNA sequencing of synchronous female bilateral breast cancers

  Study EGAS00001006910

• RNA sequencing of chondrosarcoma

  To profile chondrosarcoma patients.

  Study EGAS00001004585

• Comprehensive genomic analysis of patient derived orthotopic xenograft model in primary central nervous system lymphoma

  The purpose of this study is to investigate genetic background of orthotopic xenograft cells and aseess consistency with parent tumor cells. For exome sequencing, we used two distinct PCNSL cells (YML9 and YML11). We also performed RNA sequencing for 7 PCNSL patient tumor cells to compare NF-kB pathway activation.

  Study JGAS000178

• An Advanced Molecular Medicine Case Report of a Rare Human Tumor Using Genomics, Pathomics, and Radiomics

  The associated data of this study is derived from a single female patient with pulmonary sclerosing pneumocytoma (PSP). The aim of this study is to provide the most comprehensive, multi-modality sequencing study of a single case of PSP to-date. To this end, the following sequencing experiments were performed: i) RNA-Seq of the primary tumor and adjacent normal tissues (6 replicates for each tissue type), which was intended to analyze RNA-Seq fusions, gene expression, expression mutations, ii) low-pass DNA whole genome sequencing (WGS) from primary tumor tissue and germline, which was intended to analyze copy number aberrations, and iii) DNA targeted panel sequencing of lung cancer associated genes, using primary tumor tissue and germline from white blood cells, which was intended to analyze somatic mutations. Principal findings: i) the PSP hallmark mutation AKT1 (p.E17K) was detected within both the DNA and RNA, and ii) the TP53 signaling pathway was found to be statistically significant by three different pathway analysis tools of analyzing gene expression and pathway ramifications. Among proteins within the TP53 signaling pathway, the p53 inhibitor encoded by MDM2 was found to be overexpressed (by differential gene expression analysis). The original sequencing data (i.e., FastQ files) from each of the aforementioned samples will be accessible through dbGaP.

  Study phs003154

• Differential Gene Expression in Cryptorchid Testes

  Differential Gene Expression in Cryptorchid Testes Study uses whole-genome RNA profiling of testicular biopsies to determine a potential causative role of isolated congenital cryptorchidism in azoospermia and/or infertility in the context of our previously published GeneChip data. Cryptorchid patients, aged 7 months to 5 years and otherwise healthy, were enrolled in this prospective study. During surgery, testicular tissue biopsies were obtained for histological examination and RNA-sequencing (RNA-seq). Fifteen patients were selected based on the histological results and were divided into two groups. Seven were classified as belonging to the high infertility risk (HIR) and eight to the low infertility risk (LIR) group. Cryptorchid boys in the high infertility risk group lacked transformation of gonocytes into Ad spermatogonia due to impaired mini puberty. This group of patients will be infertile despite successful surgery.

  Study phs001275

• Genomic Analysis of Low Grade B-Cell Lymphoma

  We included tumors from 64 newly diagnosed or untreated Low Grade B-Cell Lymphoma (LGBCL) patients, consisting of SMZL (n = 48), NMZL (n = 6), EMZL (n = 2), LPL (n = 5), and B-NOS (n = 3) in this study. Samples were selected from cases consented to the Molecular Epidemiology Resource (MER) of the University of Iowa and Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). RNA or DNA were extracted from 64 frozen LGBCLs tumors (with available matched germline DNA for N=61. For RNA sequencing, library preparation was done using the Illumina TruSeq RNA Exome Kit and sequenced with 100 nucleotide paired-end reads using the HiSeq 4000. For WES, library preparation was done using the Agilent SureSelect XT kit and sequenced with 100 nucleotide paired-end reads using the Illumina HiSeq 4000.

  Study phs002552

• Single-cell RNA sequencing of human omental tissue in benign and metastatic ovarian cancer

  To elucidate the cellular and molecular mechanisms underlying omental homeostasis and its transformation during ovarian cancer metastasis, a human omental cell atlas was generated encompassing both benign and metastatic conditions. Single-cell RNA sequencing was performed on freshly dissociated omental tissue samples from patients with newly diagnosed benign and malignant disease. Samples collected during diagnostic surgery covered distinct anatomical regions, enabling comparison between non-metastasized omentum and sites along the metastatic gradient, including distant, peritumoral, and tumor core areas.

  Study EGAS50000001465

• Deep RNA sequencing in CLL

  Chronic lymphocytic leukemia (CLL) is a B-cell neoplasm with a heterogeneous clinical and biological behavior. We have performed deep RNA sequencing in different subpopulations of B-lymphocytes from healthy individuals and CLL cells from a cohort of 98 patients, and characterized the CLL transcriptional landscape with unprecedented resolution. The transcriptomic architecture of CLL uncovered here refines the biological characterization of the disease and opens new perspectives for the clinical management of patients.

  Study EGAS00001000374

• Single-cell RNA sequencing reveals cell-type specific eQTLs in peripheral blood mononuclear cells

  This proof-of-concept study shows that single-cell RNA sequencing in ~25,000 peripheral blood mononuclear cells (PBMCs) of 45 donors allows for the identification of cell type-specific cis expression quantitative trait loci effects (cis-eQTLs). Moreover, the significant top-eQTL effects show consistent allelic direction (94%) with previously published whole blood deepSAGE data. These cell type-specific eQTLs may give us additional insight into the downstream consequences of genetic risk factors for immune-mediated diseases.

  Study EGAS00001002560

• Illumina RNA sequencing for HLA expression qauntification

  In this study, we quantified mRNA expression levels of HLA class I and II genes from peripheral blood samples of 50 healthy individuals. The gene- and allele-specific mRNA expression was assessed using unique molecular identifiers, which enabled PCR bias removal and calculation of the number of original mRNA transcripts. We identified differences in mRNA expression between different HLA genes and alleles. Our results suggest that HLA alleles are differentially expressed and these differences in expression levels are quantifiable using RNA sequencing technology.

  Study EGAS00001004931

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015713

• Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET)

  STARNET is a genetics of RNA expression study of multiple disease-relevant tissues obtained from living patients with cardiovascular disease. Tissue samples are obtained from blood, atherosclerotic-lesion-free internal mammary artery (MAM) and atherosclerotic aortic root (AOR), subcutaneous fat (SF), visceral abdominal fat (VAF), skeletal muscle (SKLM), and liver (LIV) during open thorax surgery of 600 coronary artery disease (CAD) patients. All patients gave written informed consent. The inclusion criterion was eligibility for coronary artery by-pass graft (CABG) surgery. Patients with other severe systemic diseases, such as active systemic inflammatory disease or cancer, were excluded. The primary clinical end points were the SYNTAX score based on the extent of coronary atherosclerosis assessed from preoperative angiograms. The STARNET patients are Caucasians (31% females); 32% had diabetes, 75% had hypertension, and 67% had hyperlipidemia; and 33% had an MI before age 60. By New York Heart Association criteria, 45% were class I, 42% class II, 9% class III, and 1% class IV. TYPES AND RNA SEQUENCING: 566 DNA genotype and 3577 RNA-seq profiles from seven tissues from 600 STARNET CABG patients passed quality control (on average 511 RNA-seq profiles/tissue). DNA was genotyped with the OmniExpress Exome array (Illumina, ~900k SNPs) and imputed to a total of 14,098,063 DNA variant calls (6,245,505 with minor allele frequency >5%). The STARNET subjects mainly overlap with Caucasian of Northern European (Finnish) descent. RNA sequencing was performed using the HighSeq2000 platform, poly-A (LIV, SKLM, VAF, SF and blood) and ribo-zero (AOR, MAM) protocols with 50-100 bp read lengths, single end to 15-30 million read depth.

  Study phs001203

• RNA sequencing data of 66 matched primary and recurrent high grade serous ovarian cancer

  Dac EGAC00001000741

• Targeted RNA sequencing of breast cancer GWAS loci

  Dataset EGAD00001004498

• Chordoma_Sequencing_Project_Whole_Genome

  This is a continuation of the Chordoma Sequencing Project, prelim #G0175-122-CF. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. The Chordoma Foundation will fund the RNA Sequencing/Methylation and SNP6 costs for this project while the whole genome and library sequencing will be covered under the CGP, 2012-2013 core WTSI internal funding. An additional sequencing of three cancer cell lines will be added to this work, financed by the Chordoma Foundation. In this project, the Chordoma foundation will pay for the additional costs of methylation, RNA Seq,

  Study EGAS00001000409

• ChIIP-seq and RNA-seq

  epigenome profiling in tumor tissues and paired normal tissues of LUAD patients and transcriptome profiling in tumor tissues of LUAD patients.

  Dataset EGAD00001007066

• Single cell RNA sequencing of 33 primary colorectal cancer

  Study EGAS00001003779